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Meteorological Processes Affecting Air Quality – Research and Model Development Needs
Citation:
Pleim, Jon AND S. McKeen. Meteorological Processes Affecting Air Quality – Research and Model Development Needs. EM: AIR AND WASTE MANAGEMENT ASSOCIATION'S MAGAZINE FOR ENVIRONMENTAL MANAGERS. Air & Waste Management Association, Pittsburgh, PA, 9:52-55, (2012).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s)Atmospheric Modeling Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were developed over the past several decades primarily for forecasting the weather. While many of the same characteristics and processes are important for both weather forecasting and for air quality modeling, there are particular meteorological conditions, such as stagnant high pressure systems and convergence zones associated with occluded fronts, which are especially conducive to air pollution episodes, but are of lesser interest to weather forecasters. Furthermore, there is general recognition that many of the greatest uncertainties in air quality modeling systems stem from uncertainties in the dynamical and thermodynamic processes simulated by meteorological models.
URLs/Downloads:
FINAL FINAL ARTICLE5_WORKSHOP_PLEIM_MCKEEN.PDF (PDF, NA pp, 120.597 KB, about PDF)EM Magazine
